This book comprehensively discusses the modeling of real-world industrial problems and innovative optimization techniques such as heuristics, finite methods, operation research techniques, intelligent algorithms, and agent- based methods.
- Discusses advanced techniques such as key cell, Mobius inversion, and zero suffix techniques to find initial feasible solutions to optimization problems.
- Provides a useful guide toward the development of a sustainable model for disaster management.
- Presents optimized hybrid block method techniques to solve mathematical problems existing in the industries.
- Covers mathematical techniques such as Laplace transformation, stochastic process, and differential techniques related to reliability theory.
- Highlights application on smart agriculture, smart healthcare, techniques for disaster management, and smart manufacturing.
Advanced Mathematical Techniques in Computational and Intelligent Systems
is primarily written for graduate and senior undergraduate students, as well as academic researchers in electrical engineering, electronics and communications engineering, computer engineering, and mathematics.
This book comprehensively discusses the modeling of real-world industrial problems and innovative optimization techniques such as heuristics, finite methods, operation research techniques, intelligent algorithms, and agent-based methods.
1. Increasing the order of convergence of three step modified
Potra-Ptak-Chebyshev methods for systems and equations.
2. Mathematical model
to distinguish the symptomatic patient of COVID-19.
3. Maximum cost cell
Method for IBFS of Transportation Problems.
4. Optimization Techniques and
Applications to Solve Real-World Industrial Optimization Problems.
5. A
Method to Solve Trapezoidal Transshipment Problem under Uncertainty.
6.
Enhancing the Security of Public Key Cryptographic Model based on Integrated
ElGamal-Elliptic Curve Diffe Hellman (EG-ECDH) Key Exchange Technique.
7. An
investigation of fractional ordered biological systems using a robust
semi-analytical technique.
8. Variable Selection in Multiple Nonparametric
Regression Modelling.
9. Mathematical Modeling of Regulation of Sulfur
Metabolic Pathways.
10. Some Results on Quasi Convergence in Gradual Normed
Linear Spaces.
11. On Einstein Gyrogroup.
12. On the norms of Toeplitz and
Hankel matrices with balancing and Lucas-balancing numbers.
13. Grey Wolf
Optimizer for the design optimization of a DC-DC Buck Converter.
14. A new
modified Iterative Transform Method for solving time-fractional nonlinear
dispersive Korteweg-de Vries equation.
15. Application of Graph Theory in
Search of Websites and Web Pages.
Dr. Sandeep Singh is an Assistant Professor at the Department of Mathematics at Akal University Talwandi Sabo, Bathinda, Punjab, India. He received his Ph.D. in Group Theory (Mathematics) from School of Mathematics, Thapar University, Patiala, India.
Prof. Aliakbar Montazer Haghighi is a Professor at the Department of Mathematics, Prairie View A&M University, Texas, USA. He received his Ph.D. degree from Case Western Reserve University, Cleveland, Ohio, USA.
Dr. Sandeep Dalal is a postdoctoral fellow at NISER, Bhubaneshwar, Orrisa, India. He received his Ph.D in algebraic graph theory from the Department of Mathematics, Birla Institute of Technology and Science, Pilani, India.
